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A real-time yoga pose estimation system using MediaPipe for landmark extraction and Support Vector Machines (SVM) for pose classification. Designed for accessibility via a standard webcam, the system provides instant feedback on pose accuracy, suggests corrections, and tracks user progress. Key features include personalized pose calibration, real-time feedback, and an intuitive interface. The system addresses challenges in real-time tracking and shows strong potential for virtual fitness applications.

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Real-Time Yoga Pose Estimation System Using MediaPipe and SVM for Desktop-Based Feedback and Correction

  • 会议论文

  • 发表日期：

    2026年

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  • Muhammad Asfand Yar Amjad,
  • Muhammad Khalid,
  • Honyu Wu

摘要

A real-time yoga pose estimation system using MediaPipe for landmark extraction and Support Vector Machines (SVM) for pose classification. Designed for accessibility via a standard webcam, the system provides instant feedback on pose accuracy, suggests corrections, and tracks user progress. Key features include personalized pose calibration, real-time feedback, and an intuitive interface. The system addresses challenges in real-time tracking and shows strong potential for virtual fitness applications.